Jonathan Sidi, Metrum Research Group
We are happy to bring the slick JavaScript library to R. It is self-described as “the last carousel you’ll ever need”. This carousel is based on putting the elements of the carousel in a div HTML tag. This makes the carousel very versatile in what can be placed inside. Regular objects that are placed in a carousel can be for example: images, plots, tables, gifs, videos, iframes and even htmlwidgets.
This tool helps review multiple outputs in an efficient manner and saves much needed space in documents and Shiny applications, while creating a user friendly experience.
These carousels can be used directly from the R console, from RStudio, in Shiny apps and R Markdown documents.
install.packages('slickR')
Githhub (dev)
devtools::install_github('metrumresearchgroup','slickR')
Some web scraping for the images example….
#NBA Team Logos
nbaTeams=c("ATL","BOS","BKN","CHA","CHI","CLE","DAL","DEN","DET","GSW",
"HOU","IND","LAC","LAL","MEM","MIA","MIL","MIN","NOP","NYK",
"OKC","ORL","PHI","PHX","POR","SAC","SAS","TOR","UTA","WAS")
teamImg=sprintf("https://i.cdn.turner.com/nba/nba/.element/img/4.0/global/logos/512x512/bg.white/svg/%s.svg",nbaTeams)
#Player Images
a1=read_html('http://www.espn.com/nba/depth')%>%html_nodes(css = '#my-teams-table a')
a2=a1%>%html_attr('href')
a3=a1%>%html_text()
team_table=read_html('http://www.espn.com/nba/depth')%>%html_table()
team_table=team_table[[1]][-c(1,2),]
playerTable=team_table%>%melt(,id='X1')%>%arrange(X1,variable)
playerName=a2[grepl('[0-9]',a2)]
playerId=do.call('rbind',lapply(strsplit(playerName,'[/]'),function(x) x[c(8,9)]))
playerId=playerId[playerId[,1]!='phi',]
playerTable$img=sprintf('http://a.espncdn.com/combiner/i?img=/i/headshots/nba/players/full/%s.png&w=350&h=254',playerId[,1])
Let’s start easy: show the team logos one at a time with dots underneath
slickR(obj = teamImg,slideId = 'ex1',height = 100,width='100%')
There are players on each team, so lets group the starting five together and have each dot correspond with a team:
slickR(
obj = playerTable$img,
slideId = c('ex2'),
slickOpts = list(
initialSlide = 0,
slidesToShow = 5,
slidesToScroll = 5,
focusOnSelect = T,
dots = T
),
height = 100,width='100%'
)
Sometimes the dots won’t be informative enough so we can switch them with an HTML object, such as text or other images. We can pass to the customPaging argument javascript code using the htmlwidgets::JS function.
cP1=JS("function(slick,index) {return '<a>'+(index+1)+'</a>';}")
slickR(
obj = playerTable$img,
slideId = 'ex3',
dotObj = teamImg,
slickOpts = list(
initialSlide = 0,
slidesToShow = 5,
slidesToScroll = 5,
focusOnSelect = T,
dots = T,
customPaging = cP1
),
height=100,width='100%'
)
cP2=JS("function(slick,index) {return '<a><img src= ' + dotObj[index] + ' width=100% height=100%></a>';}")
#Replace dots with Images
s1 <- slickR(
obj = playerTable$img,
dotObj = teamImg,
slickOpts = list(
initialSlide = 0,
slidesToShow = 5,
slidesToScroll = 5,
focusOnSelect = T,
dots = T,
customPaging = cP2
),height = 200,width='100%'
)
#Putting it all together in one slickR call
s2 <- htmltools::tags$script(
sprintf("var dotObj = %s", jsonlite::toJSON(teamImg))
)
htmltools::browsable(htmltools::tagList(s2, s1))
To place plots directly into slickR we use svglite to convert a plot into svg code using xmlSVG and then convert it into a character object
plotsToSVG=list(
#Standard Plot
xmlSVG({plot(1:10)},standalone=TRUE),
#lattice xyplot
xmlSVG({print(xyplot(x~x,data.frame(x=1:10),type="l"))},standalone=TRUE),
#ggplot
xmlSVG({show(ggplot(iris,aes(x=Sepal.Length,y=Sepal.Width,colour=Species))+
geom_point())},standalone=TRUE),
#lattice dotplot
xmlSVG({print(dotplot(variety ~ yield | site , data = barley, groups = year,
key = simpleKey(levels(barley$year), space = "right"),
xlab = "Barley Yield (bushels/acre) ",
aspect=0.5, layout = c(1,6), ylab=NULL))
},standalone=TRUE)
)
#make the plot self contained SVG to pass into slickR
s.in=sapply(plotsToSVG,function(sv){paste0("data:image/svg+xml;utf8,",as.character(sv))})
slickR(s.in,slideId = 'ex4',slickOpts = list(dots=T), height = 200,width = '100%')
There are instances when you have many outputs at once and do not want to go through all, so you can combine two carousels one for viewing and one for searching.
slickR(rep(s.in,each=5),slideId = c('ex5up','ex5down'),
slideIdx = list(1:20,1:20),
synchSlides = c('ex5up','ex5down'),
slideType = rep('img',4),
slickOpts = list(list(slidesToShow=1,slidesToScroll=1),
list(dots=F,slidesToScroll=1,slidesToShow=5,
centerMode=T,focusOnSelect=T)
),
height=100,width = '100%'
)
Since the carousel can accept any html element we can place iframes in the carousel.
There are times when you may want to put in different DOMs rather than an image in slick. Using slideType you can specify which DOM is used in the slides.
For example lets put the help Rd files from ggplot2 into a slider using the helper function getHelp. (Dont forget to open the output to a browser to view the iframe contents).
geom_filenames=ls("package:ggplot2",pattern = '^geom')
slickR(unlist(lapply(geom_filenames,getHelp,pkg = 'ggplot2')),slideId = 'ex6',slideType = 'iframe',height = '400px',width='100%',slickOpts = list(dots=T,slidesToShow=2,slidesToScroll=2))
Finally, we can really leverage R and place self contained htmlwidgets in iframes (like leaflets and plotly) and use them in a carousel. This solves a problem of how to run many htmlwidgets at once outside of Shiny.
suppressMessages({
library(leaflet)
library(plotly)
})
l <- leaflet() %>% addTiles()
htmlwidgets::saveWidget(l,'leaflet.html')
p <- iris%>%ggplot(aes(x=Sepal.Length,y=Sepal.Width))+geom_point()
pL= ggplotly(p)
htmlwidgets::saveWidget(pL,'ggplotly.html')
slickR(c(rep(paste0(readLines('leaflet.html'),collapse='\n'),4),
rep(paste0(readLines('ggplotly.html'),collapse='\n'),4)),
slideId = c('leaf','plot'),
slideIdx = list(1:4,5:8),
slideType = rep('iframe',2),
slickOpts = list(list(dots=T,slidesToShow=2,slidesToScroll=2),
list(dots=T,slidesToShow=2,slidesToScroll=2)),
height='400px',width='100%')